1. Field of the Invention
This invention relates generally to analysis of the activity of chemical reaction networks and, more specifically, to computational methods for simulating and predicting the activity of Homo sapiens (Human) reaction networks.
2. Background Information
Metabolism is vital to organism function and survival, and it is connected to essentially all aspects of cellular function in both physiological and patho-physiological states. Therefore, it is not surprising that metabolism is a key contributor to several important human diseases, including diabetes, obesity, cardiovascular disease, and cancer. Since metabolism has been carefully studied for decades in a variety of organisms, there is a collective knowledge base available that includes a legacy of valuable data, including many mechanistic reactions and well-characterized interactions. The procedure for integrating these data into a network reconstruction and predictive model has been well established for microorganisms and has recently been extended to mouse cellular metabolism (Sheikh, K., Forster, J. & Nielsen, L. K. Modeling hybridoma cell metabolism using a generic genome-scale metabolic model of Mus musculus. Biolechnol Prog 21, 112-21 (2005); Reed, J. L., Famili, I., Thiele, I. & Palsson, B. O. Towards multidimensional genome annotation. Nat Rev Genet 7, 130-41 (2006)).
It has been shown that even relatively minor changes in media composition can affect hundreds of components of these networks such that potentially hundreds of variables are worthy of consideration in making a prediction of cellular behavior. Similarly, due to the complexity of interactions in these networks, mutation of even a single gene can have effects on multiple components of the networks.
Thus, there exists a need for a model that describes Human reaction networks, such as the human metabolic network, which can be used to simulate many different aspects of cellular behavior under different conditions. The present invention satisfies this need, and provides related advantages as well. As such, the wealth of detailed biochemical information available for humans, combined with the recent sequencing and annotation of the human genome sequence (Finishing the euchromatic sequence of the human genome. Nature 431, 931-45 (2004)), has enabled the first comprehensive, bottom-up reconstruction of the global human metabolic network.